概要: Amazon's automated performance evaluation system involving AI-powered cameras incorrectly punished delivery drivers for non-existent mistakes, impacting their chances for bonuses and rewards.
Alleged: Netradyne developed an AI system deployed by Amazon, which harmed Amazon delivery drivers と Amazon workers.
CSETv1 分類法のクラス
分類法の詳細Incident Number
The number of the incident in the AI Incident Database.
116
Risk Subdomain
A further 23 subdomains create an accessible and understandable classification of hazards and harms associated with AI
7.3. Lack of capability or robustness
Risk Domain
The Domain Taxonomy of AI Risks classifies risks into seven AI risk domains: (1) Discrimination & toxicity, (2) Privacy & security, (3) Misinformation, (4) Malicious actors & misuse, (5) Human-computer interaction, (6) Socioeconomic & environmental harms, and (7) AI system safety, failures & limitations.
- AI system safety, failures, and limitations
Entity
Which, if any, entity is presented as the main cause of the risk
AI
Timing
The stage in the AI lifecycle at which the risk is presented as occurring
Post-deployment
Intent
Whether the risk is presented as occurring as an expected or unexpected outcome from pursuing a goal
Unintentional
インシデントレポート
レポートタイムライン
“Maintain safe distance,” the camera installed above his seat would say when a car cut him off. That data would be sent to Amazon, and would be used to evaluate his performance that week and determine whether he got a bonus.
In early 2021, …
Concerns about artificial intelligence and its impact on work are not new, but as more companies deploy these solutions we’re seeing decided snags in the process. One point many of these conversations take for granted is that AI-powered too…
バリアント
「バリアント」は既存のAIインシデントと同じ原因要素を共有し、同様な被害を引き起こし、同じ知的システムを含んだインシデントです。バリアントは完全に独立したインシデントとしてインデックスするのではなく、データベースに最初に投稿された同様なインシデントの元にインシデントのバリエーションとして一覧します。インシデントデータベースの他の投稿タイプとは違い、バリアントではインシデントデータベース以外の根拠のレポートは要求されません。詳細についてはこの研究論文を参照してください
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よく似たインシデント
Did our AI mess up? Flag the unrelated incidents